:

Ratika Srivastava1, Lauran Cole1, Kimberly Amador1

  • 1From the Division of Pediatric Neurology (R.S., L.C.), Department of Pediatrics, University of Alberta; Alberta Children's Hospital Research Institute and Department of Clinical Neurosciences (K.A.); Department of Clinical Neurosciences (N.D.F.); Department of Pediatrics and Clinical Neurosciences (M.D.), University of Calgary, Alberta; Departments of Pediatrics and Neurology/Neurosurgery (M.I.S., M.O.), McGill University, Montreal, Quebec, Canada; Newcastle upon Tyne Hospitals (A.P.B.), NHS Foundation Trust, Newcastle upon Tyne, United Kingdom; Department of Neurology (M.J.R.), Boston Children's Hospital and Department of Neurology, Harvard Medical School, Boston, MA; Department of Neonatology (E.S.), Soroka University Medical Center and Faculty of Health sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel; Department of Neonatology (L.S.V.), University Medical Center Utrecht, The Netherlands; Departments of Pediatrics and Community Health Sciences (D.D.), Owerko Centre at the Alberta Children's Hospital Research Institute, Hotchkiss Brain Institute, Cummings School of Medicine; Faculty of Nursing and Cumming School of Medicine (N.L.), Departments of Pediatrics, Psychiatry and Community Health Sciences; Alberta Children's Hospital Research Institute and Department of Clinical Neurosciences (P.M.); Departments of Clinical Neurosciences (M.D.H.), Community Health Sciences, Medicine and Radiology, Hotchkiss Brain Institute and Department of Pediatrics (A.K.), Cumming School of Medicine, University of Calgary, Alberta, Canada.

Neurology
|May 15, 2024
PubMed
概括

机器学习确定了围产动脉缺血性中风 (PAIS) 的关键临床因素,这是脑的主要原因. 这种数据驱动的方法准确地预测了新生儿的PAIS风险,优于传统模型.